Automatic target recognition-type image processing systems are specialized object recognition-type image processing systems that provide the capability to detect and recognize targets (or objects), and assist with the launch of weapons against targets. As imaging technology has matured, the ability to reduce pilot workload using automatic target recognition-type image processing systems in single-seat, high-performance aircraft has evolved. The same maturation process has resulted in significant improvements in ground-to-air defense systems, and has decreased the time available for a pilot to detect and recognize targets and launch weapons.
A viable approach to minimizing aircraft exposure to enemy fire and to minimizing pilot workload under combat conditions, while maximizing the range within which a pilot can launch weapons, is to employ automatic target recognition technology incorporating the advances in imaging technology in the aircraft. Generally, automatic target recognition processes require six operations. During a first operation, an image sensor (e.g., a charge coupled device) mounted in the aircraft scans an area on the surface of the earth below the aircraft and produces an image of that area. The image is composed of many pixels; the number of pixels is determined by the size of the image sensor.
A second operation is image enhancement, during which the image produced by the sensor is enhanced by eliminating background noise and other non-uniformities in the image. A third operation is called target segmentation. Target segmentation includes identifying pixels of the image that form possible targets (including the edge of each target) and background pixels. This process requires extremely sophisticated segmentation processing (including many calculations) over the entire input image.
During a fourth operation of target detection, targets in the segmented image are detected ("prescreened"). During a fifth operation, features of the image as they relate to the identified targets are extracted from the image. Feature extraction includes the process of extracting certain characteristics of each target in the image (e.g., average gradient over the object perimeter).
Finally, during a sixth operation each target in the image is classified or identifying as being a member of a particular class of targets based upon a given set of target characteristics (e.g., a tank class).
The problem with incorporating conventional automatic target recognition technology in aircraft is that current approaches to target segmentation, detection, and classification involve the use of hardware developed for high-end recognition systems. These high-end recognition systems are large (greater than one cubic foot), making it difficult for them to fit in the limited space typically available in aircraft. These systems are also extremely complicated, and the large number of operations they perform make it difficult for them to complete their operations in the limited time available under combat conditions. Moreover, conventional high-end recognition systems require a great deal of power to operate, and such power generally is not available on the typical aircraft.
Accordingly, alternative automatic target recognition systems have been developed which use compact hardware systems capable of performing the functions of high-end target recognition systems. These compact hardware systems consume less power than is traditionally required by high-end target recognition systems. The size of these compact hardware systems facilitate their use in aircraft. However, these conventional target recognition systems still include the prohibitively large number of operations generally required by conventional high-end target recognition systems. The large number of operations makes it difficult for all operations to be completed within the limited time a pilot has under combat conditions.